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Abstract

Deriving valid inferences about the causes and consequences of dispersal from empirical studies depends largely on our ability reliably to estimate parameters associated with dispersal. Here, we present a review of the methods available for estimating dispersal and related parameters using marked individuals. We emphasize methods that place dispersal in a probabilistic framework. In this context, we define a dispersal event as a movement of a specified distance or from one predefined patch to another, the magnitude of the distance or the definition of a `patch? depending on the ecological or evolutionary question(s) being addressed. We have organized the chapter based on four general classes of data for animals that are captured, marked, and released alive: (1) recovery data, in which animals are recovered dead at a subsequent time, (2) recapture/resighting data, in which animals are either recaptured or resighted alive on subsequent sampling occasions, (3) known-status data, in which marked animals are reobserved alive or dead at specified times with probability 1.0, and (4) combined data, in which data are of more than one type (e.g., live recapture and ring recovery). For each data type, we discuss the data required, the estimation techniques, and the types of questions that might be addressed from studies conducted at single and multiple sites.